4 papers
TRIM: Scalable 3D Gaussian Diffusion Inference with Temporal and Spatial Trimming
Zeyuan Yin, Xiaoming Liu
Recent advances in 3D Gaussian diffusion models suffer from time-intensive denoising and post-denoising processing due to the massive number of Gaussian primitives, resulting in sl…
DELT: A Simple Diversity-driven EarlyLate Training for Dataset Distillation
Zhiqiang Shen, Ammar Sherif, Zeyuan Yin +1
Recent advances in dataset distillation have led to solutions in two main directions. The conventional batch-to-batch matching mechanism is ideal for small-scale datasets and inclu…
Dataset Distillation via Curriculum Data Synthesis in Large Data Era
Zeyuan Yin, Zhiqiang Shen
Dataset distillation or condensation aims to generate a smaller but representative subset from a large dataset, which allows a model to be trained more efficiently, meanwhile evalu…
Self-supervised Dataset Distillation: A Good Compression Is All You Need
Muxin Zhou, Zeyuan Yin, Shitong Shao +1
Dataset distillation aims to compress information from a large-scale original dataset to a new compact dataset while striving to preserve the utmost degree of the original data inf…